De-interlacing has become an important technique because of the popularity of progressive scan television devices. Since the invention of television more than 70 years ago, the interlaced scan has been used exclusively due to a tradeoff between frame rate and transmission bandwidth utilization. The interlaced scan doubles the frame rate as compared with a progressive scan, allowing still or slow-moving areas to be perceived with higher vertical detail, while fast-moving areas are perceived with a higher temporal rate at half vertical resolution. However, if an interlaced-scan video is directly shown on progressive devices, defects like line crawling, edge-flicker, and jagged edges appear and make the viewer uncomfortable.
De-interlacing is conventionally accomplished using a software approach or a hardware approach. BOB and Weave are two low-complexity de-interlacing methods commonly adopted in the software approaches. BOB is an intra-field interpolation method that uses a single field to reconstruct one progressive frame. However, the vertical resolution is halved and the image is blurred using the BOB method. Weave is a simple inter-field de-interlacing method directly combining two interlaced fields into a single progressive frame. However, the line-crawling effect will arise in motion areas created with Weave.
For hardware-base de-interlacing approaches, motion adaptive methods are commonly used in consumer electronics. The basic concept is to select an appropriate interpolation method according to the motion in different areas of an image. In particular, spatial filtering is selected in motion areas and temporal filtering is selected in static areas. Hence, the motion adaptive de-interlacing method combines the advantages of both intra-field de-interlacing and inter-field de-interlacing. However, some motion detection errors still exist with the conventional motion adaptive methods.
The most advanced hardware de-interlacing methods use a motion compensation scheme where the interpolation is performed along a motion trajectory. The conventional motion compensation methods are useful for getting high resolution and flicker-free pictures in motion areas. However, the motion compensation approaches are highly dependent on the accuracy of motion estimation, which results in high hardware complexity. In particular, sub-pixel accuracy is a condition to reflect the true motion of an object. However, too many sub-pixel interpolations fail to retain true image resolution.